Portable digital projectors are now common. These projectors can display large format images and videos. Typically, the projector is positioned on a table, located in a projection booth, or mounted on the ceiling.
In the prior art, the optical axis of the projectors must be orthogonal to a planar display surface to produce an undistorted image. In addition, a lateral axis of the projector must be horizontal to obtain a level image. Even if the above constraints are satisfied, it is still difficult, or even impossible, given physical constraints of the projection environment, to perfectly align a projected image with a predefined target image area on the projection surface. If the projector is placed causally, then image correction is required.
A complete correction for a planar display surface needs to consider three degrees of positional freedom, two degrees of scalar freedom, and three degrees of rotational freedom to minimize distortion. These corrections may be insufficient if the display surface is an arbitrary manifold. Hereinafter, the term manifold refers specifically to a topological connected surface having an arbitrary shape and pose in three dimensions. Pose means orientation and position.
It is possible to distort the image to be projected so that the projected image appears correctly aligned and undistorted. However, this requires that the projector be carefully calibrated to the display surface. This calibration process can be time-consuming and tedious when done manually and must be performed frequently to maintain a quality image. For a dynamic display environment, where either the projector or the display surface or both are moving while projecting, this is extremely difficult.
Most prior art automatic calibration techniques are severely limited in the number of degrees of freedom that can be corrected, typically only one or two degrees of keystone correction. They are also limited to planar display surfaces. Prior art techniques that have been capable of automatically correcting for position, size, rotation, keystone distortion as well as irregular surfaces have relied on knowledge of the absolute or relative geometry data of the room, the display surface, and calibration cameras. When a camera is used for calibration, the display surface must be reflective to reflect the calibration pattern to the camera. A number of techniques require modifications to the projector to install tilt sensors.
The disadvantages of such techniques include the inability to use the projector when or where geometric calibration data are not available, or when non-projector related changes are made, such as a repositioning or reshaping the display surface or changing the calibration cameras. When the display surface is non-reflective, or when the display surface is highly reflective, which leads to confusing specular highlights, camera based calibrations systems fail. Also, with camera based systems it is difficult to correlate pixels in the camera image to corresponding pixels in the projected image.
Therefore, there is a need for a fully automated method for calibrating a projector to an arbitrarily shaped surface.